Rough sets approach to symbolic value partition

AbstractIn data mining, searching for simple representations of knowledge is a very important issue. Attribute reduction, continuous attribute discretization and symbolic value partition are three preprocessing techniques which are used in this regard. This paper investigates the symbolic value partition technique, which divides each attribute domain of a data table into a family for disjoint subsets, and constructs a new data table with fewer attributes and smaller attribute domains. Specifically, we investigates the optimal symbolic value partition (OSVP) problem of supervised data, where the optimal metric is defined by the cardinality sum of new attribute domains. We propose the concept of partition reducts for this problem. An optimal partition reduct is the solution to the OSVP-problem. We develop a greedy algorithm to search for a suboptimal partition reduct, and analyze major properties of the proposed algorithm. Empirical studies on various datasets from the UCI library show that our algorithm effectively reduces the size of attribute domains. Furthermore, it assists in computing smaller rule sets with better coverage compared with the attribute reduction approach

How Does Fundraiser-claimed Product Innovation Influence Crowdfunding Outcomes

The crowdfunding platforms have always been dedicated to supporting and inspiring innovative, and creative campaigns. However, limited research has been done to examine the fundraiser-claimed product innovation in campaign descriptions and its relation to fundraising performance. In this paper, we aim to tackle this important yet understudied problem. More specifically, we adopt a deep learning-based approach to extract sentences that contain innovation claims from project descriptions. We then conduct an empirical analysis to study the relation between fundraiser-claimed product innovation and crowdfunding performance by using a large sample consisting of 11,521 projects collected from Kickstarter across 4 project categories. Findings show a statistically significant association between fundraiser-claimed product innovation and crowdfunding performance. Additionally, the number of focal project innovation claims has a curvilinear relationship (inverted ‘U’ shape) with crowdfunding performance. Our study contributes to both product innovation detection and crowdfunding literature by demonstrating the association between product innovation presentation and crowdfunding performance

Stochastic Electron Acceleration in Shell-Type Supernova Remnants II

We discuss the generic characteristics of stochastic particle acceleration by a fully developed turbulence spectrum and show that resonant interactions of particles with high speed waves dominate the acceleration process. To produce the relativistic electrons inferred from the broadband spectrum of a few well-observed shell-type supernova remnants in the leptonic scenario for the TeV emission, fast mode waves must be excited effectively in the downstream and dominate the turbulence in the subsonic phase. Strong collisionless non-relativistic astrophysical shocks are studied with the assumption of a constant Aflven speed. The energy density of non-thermal electrons is found to be comparable to that of the magnetic field. With reasonable parameters, the model explains observations of shell-type supernova remnants. More detailed studies are warranted to better understand the nature of supernova shocks.Comment: 5 pages, 7 figures, submitted to Proceedings of the Conference on "2008 Heidelberg International Symposium on High Energy Gamma-Ray Astronomy